期刊名称：Petroleum-Gas University of Ploiesti Bulletin : Economic Sciences Series
印刷版ISSN：2284-8576
电子版ISSN：2247-8582
出版年度：2015
卷号：3
页码：125-132
出版社：Petroleum-Gas University of Ploiesti
摘要：In the economical environment, most of the optimization problems are related to cost minimization or revenue maximization. In the area of multi-type goods manufacturing, the element to be determined for a maximum profit is often the production structure for a specific manufacturing time horizon. If the problem is simple (small input data and/or short time horizon), no sophisticated algorithm is needed; even empiric solutions are acceptable. But the real instances, in most of the cases, have big input data, they refer to large time horizons and frequently claim the best solutions as fast as possible. In this context, to solve such real problems, both exact and approximate optimization methods are used - from the mathematical programming to greedy methods, genetic algorithms, tabu search and model-based algorithms. Here, the genetic algorithm perspective to find the optimum manufacturing structure for a time horizon is presented and afterwards is tested on a simple problem instance. The results indicate that the genetic algorithms are a valid and efficient alternative to the classical optimization methods in many problems in economics
